Funded PhD Studentship to work with Hawk-Eye Innovations

Advances in automated video tracking and computer vision technologies have created new opportunities to better understand injury mechanisms and sporting performance in elite sport. However, there remains limited evidence regarding the utility of these systems for identifying injurious events, quantifying movement characteristics, and supporting decision-making in applied sporting environments.

This PhD project will evaluate the application of Hawk-Eye video tracking systems to identify injurious and/or optimal contact techniques across multiple sports. Initial work will focus on suspected head injuries in rugby union and rugby league, with opportunities to expand into additional sports during the programme.

The project will involve synchronising Hawk-Eye tracking data with coded video footage and other available data sources to investigate movement characteristics, impact mechanisms, and contextual factors associated with injurious and non-injurious events. The successful candidate will contribute to the development and evaluation of enhanced algorithms capable of improving the identification and classification of injury-related events and performance actions.

The programme of research will initially involve:
Applying Hawk-Eye tracking systems to describe injurious and non-injurious events in elite sport;
Comparing tracking outputs with established injury risk factors identified through video analysis and other data sources;
Synchronising tracking data with manually coded and labelled video footage to support model training and validation;
Investigating movement characteristics such as player speed, positioning, and impact angles associated with injury mechanisms;
Evaluating the utility and limitations of current tracking systems for injury surveillance and performance analysis;
Proposing and testing algorithm developments to improve the application of video tracking systems in sport.

The project is expected to generate high-impact research outputs including peer-reviewed publications, conference presentations, technical reports, and practical recommendations for sporting organisations and technology providers.

Candidate Requirements

 Applicants should possess:
A first-class or upper second-class undergraduate degree (or international equivalent) in sport science, biomechanics, computer science, data science, engineering, mathematics, or a related discipline;
A Master’s degree in a relevant area (desirable);
Experience in sports analytics, biomechanics, video analysis, coding/programming, machine learning, statistics, or performance analysis (desirable);
Strong written and verbal communication skills;
A passion for applied research with real-world sporting impact.
Experience working within elite sport, handling large datasets, or using programming languages such as Python, R, or MATLAB would be advantageous.

The core supervisory team will include researchers from Leeds Beckett University Prof. Ben Jones, Dr James Tooby and Dr Thomas Sawczuk and Hawk-Eye Innovations (Jordon Gale), alongside collaborators from partner sporting organisations.

Applicants are encouraged to discuss their proposals with a member of the supervisory team.

This studentship includes:

• Research support funding for project-related activities
• Access to world-class facilities at the Carnegie School of Sport
• A laptop will be provided

International candidates will be required to pay the international fee top up and are advised to contact our Research Admissions team  researchadmissions@leedsbeckett.ac.uk  

Stipend Value: £21,805

Stipends are tax-free and paid pro-rata in monthly payments

The successful candidates would ideally have: 2:1 or higher in a relevant undergraduate degree.

For those whose first language is not English you must also have an overall IELTS score of 7.0 with no individual score below 6.5 in order for applicants to obtain a CAS and Visa.

The PHD Studentship will be awarded to the strongest applications assessed on the applicant’s academic excellence, the strength of the research proposal and how the proposal fits with the research project.

To apply, please go to the application portal which can be found through the 'Apply Now' button.

Please make sure that you complete the application process in full and also provide the following additional information:

1. RESEARCH PROPOSAL (include title and project reference)

The proposal should align to the project summary and include a brief literature review related to this project, with an outline of the studies that you would propose to the answer the aims of the PhD (maximum 5 pages single spaced). It must include the research project title and reference.

The criteria listed below will be used in both selecting those applicants who will be called for interview and those who will be successful in securing a PGR award, and these should help you form your research proposal.

a) Context and significance of your research
Please outline the significance and originality of your proposed research, indicating:  aims, relationship to previous research in the field, research question(s) you are seeking to answer.
b) Research design and methods
Please outline the design of your proposed research, indicating: methodology and methods, a timetable for completion of the PGR award, ethical considerations that your research may raise.
c) Dissemination and impact
Please identify:  possible opportunities to disseminate your research to academic audiences during your PGR programme, the ways in which your research might be relevant outside academia.

You are strongly advised to discuss your proposal with the named Supervisor(s) before making your application.

How applications will be assessed Your application will be considered by a Carnegie School of Sport selection panel. The panel will evaluate applications based on the quality of the proposal, preparedness of the applicant and feasibility of the research project.

2. STATEMENT OF PURPOSE 
This should be a maximum of 1000 words outlining: What knowledge, skills, and training would you bring to the proposed research? This may include relevant academic study, relevant experience as a professional or practitioner, and any specific training in research skills/methods.  Why do you want to undertake this research in the Carnegie School of Sport at Leeds Beckett University. How does the proposed research relate to your career goals.

3. CV
A current CV, including your employment history or other professional experience, including internships. 

• Please state clearly that you are applying for a Carnegie School of Sport studentship and include the project reference '2026-October-HAWKEYE/CSS-PhD'.
• The closing date for applications is midnight on 3 August 2026.
• Shortlisted candidates will be invited for interview.
• We aim to hold in person interviews for shortlisted applicants the week commencing 24th August 
• For queries about applying please contact Research Admissions

Aguinaldo, A. L. et al. (2026) ‘Assessing the accuracy of in-stadium and portable multi-camera markerless motion capture for baseball pitching kinematics and kinetics’, Journal of Sports Sciences, 44(10), pp. 1374–1388. doi: 10.1080/02640414.2025.2595411. 

Martin, Z., Hendricks, S. and Patel, A., 2021. Automated tackle injury risk assessment in contact-based sports-a rugby union example. In Proceedings of the IEEE/CVF Conference on computer vision and pattern recognition (pp. 4594-4603).

Mohan M, et al. (2026) Can a novel computer vision-based framework detect head-on-head impacts during a rugby league tackle? Inj Prev. 2026 Mar 27;32(2):228-234

Owen C. et al. (2025) Evaluating the Probability of Head Acceleration Events in Elite Men's and Women's Rugby Union Match-Play: The Impact of Tackle Height and Body Position. Sports Med, 55(10), pp.2641-2657. 

Owen, C. et al. (2025) ‘Mind your head’, tackle characteristics associated with concussions in rugby league: A case-control study. Journal of Science and Medicine in Sport, 28(3), pp.214-221.

Owen, C. et al. (2026) Tackle higher or lower? Simulation to evaluate how changing the tackle height would impact the number of concussions and head acceleration events in men’s professional rugby league. British Journal of Sports Medicine, 60(10), pp.706-713.

Wang, D. and Guo, Y. (2026) A multimodal deep learning-based model for posture asymmetry recognition and sports injury risk prediction in adolescent table tennis athletes. Frontiers in Physiology, 17, p.1800522.